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Career History

He has a mathematics degree from Durham University, and a mathematics PhD from the University of Edinburgh, utilizing number theory to study the spacing distributions of quantized harmonic oscillators. He was a lecturer at Bolton University Maths Department for five years, after which two years of mathematical consultancy in industry took place, examining problems varying from satellite positioning algorithms to machine learning approaches to drug discovery. He then spent seven years at the Sanger Institute, developing statistical and mathematical techniques required to analyse cancer genomic data. He then joined the School of Computing Sciences in 2011.

Research Opportunities

Enquiries are welcome (email me) from potential PhD students. He would be keen to recruit anyone interested in stochastic processes, statistical physics, combinatorics and/or their applications to population genetic, genome rearrangement, or evolutionary processes.

Key Research Interests

Chris Greenman is part of the Computational Biology and the Machine Learning and Statistics research groups. Recent areas of interest include; the development of techniques from statistical physics applied to age-dependent branching processes, including (quantum) field theoretic methods, applications to cell populations and mutation processes, combinatorial approaches to counting and representing genomic rearrangement processes, cancer and viral evolutionary processes.